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HEK293 Cells

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CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.

BMC bioinformatics
BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accurate genome editing tool using ...

A Supervised Ensemble Approach for Sensitive microRNA Target Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs, a class of small non-coding RNAs, regulate important biological functions via post-transcriptional regulation of messenger RNAs (mRNAs). Despite rapid development in miRNA research, precise experimental methods to determine miRNA target in...

Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Nature methods
We engineered light-gated channelrhodopsins (ChRs) whose current strength and light sensitivity enable minimally invasive neuronal circuit interrogation. Current ChR tools applied to the mammalian brain require intracranial surgery for transgene deli...

Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...

PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices.

Journal of neural engineering
OBJECTIVE: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we...

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.

Cell
Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over ...

Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...

Predictable and precise template-free CRISPR editing of pathogenic variants.

Nature
Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a pre...

A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

Nature chemical biology
We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing prote...